Pregnancy complications (e.g. gestational diabetes [GDM], gestational hypertension [GHTN], and pre- eclampsia & eclampsia [PE/E] are major causes of perinatal morbidity and mortality. Studies have examined associations of air pollution with pregnancy complications, but have major limitations, including 1) reliance on birth certificates or billing/claims data where information may be missing or of questionable validity to ascertain outcomes and co-morbidities; 2) limited consideration of effect confounding and/or modification by other environmental factors; 3) air pollution exposure misclassification due to lack of residential address history; 4) focus on individual air pollutants rather than air pollutant mixtures; 5) lack of focus on the heterogeneity of the risk from air pollution by time and place of exposures, maternal conditions, other environmental factors, and sub-types of outcomes; 6) lack of understanding of the mediation pathways linking maternal co-morbidity with outcomes. We propose a 4-year study to address these limitations and advance knowledge of the impact of air pollutant mixture on pregnancy complications. We will leverage state-of-the-art spatiotemporal air pollution modeling and novel statistical methods that examine both individual and composite exposure profiles with a longitudinal (pre-conception through postpartum) pregnancy cohort of ~400,000 singleton pregnancies in 2008-2018 that result in a live birth or fetal death after 20 weeks gestation that have prospectively-recorded high quality clinical data and residential addresses from the electronic health record (EHR) of Kaiser Permanente Southern California members in 8 southern California counties. Primary outcomes are GHTN, PE/E, GDM. We will estimate individual-level air pollutant exposures (particulate matter and its composition and traffic-related pollutants using sophisticated spatiotemporal models), weather (air temperature, relative humidity, pressure), and built environment measures (greenness, walkability, noise, neighborhood resources) based on prospectively-recorded maternal addresses. Covariates we will examine include maternal comorbidities; history of previous pregnancies and outcomes; individual and contextual socioeconomic status (SES) indicators; employment during pregnancy and job classification; self-reported physical activity and smoking. Complementary statistical methods will be used to evaluate effects of exposure to a mixture of air pollutants while accounting for co-exposure to weather, built environment, and SES. We will examine effect modifications by SES, maternal factors, and other environmental exposures, and the potential mediating role of maternal factors on associations between air pollution and the outcomes. We will elucidate risk of pregnancy complications from air pollution exposure, heterogeneity of risk due to SES, maternal conditions, and other environmental factors, potential underlying mechanisms, susceptible sub-populations, and time windows of susceptibility. Identification of modifiable environmental risk factors and high-risk subpopulation may help to design targeted interventions to reduce these risks and associated adverse maternal and fetal outcomes.